Winning the battle against money laundering

Money laundering is a serious problem. It poses a significant risk not only to the financial systems but often to national security. Organized crime rings, drug cartels and terrorist organizations are becoming more sophisticated in the process of hiding the illicit origin of their money. In response to the rise in these activities worldwide, regulators have stepped up their compliance mandates.

With SAS Anti-Money Laundering, we save precious time and money every day.

Steven Verlinden
Business Analyst

Complying with ever-growing international and national regulations is a challenge for any insurance company. But when you are a midsize company, meeting these regulatory requirements can drain an insurer’s efforts for profitability and growth. ERGO Insurance of Belgium, a subsidiary of ERGO Insurance Group, met the challenge with SAS Anti-Money Laundering, which automates the exposure of suspect activity.

ERGO identifies potential criminal and terrorist activity with a system that verifies and validates all documents and scans its entire database every 24 hours. The key, says ERGO Business Analyst Steven Verlinden, is better analysis of the data that the company has. Now, the solution doesn’t spit out false alerts or miss suspicious individuals who try to fly under the radar by using nicknames or different spellings of the same name.

Regulation spreads its wings

What began as regulators’ efforts to target money laundering in bank accounts has expanded to comprise all types of financial instruments, including the kinds of insurance policies ERGO sells. And while ERGO Insurance Group is one of the largest insurance groups in Europe, the Benelux subsidiary only employs about 350 people.

ERGO specializes in life insurance products for individuals and the self-employed. “We must meticulously check every contract against extensive blacklists of suspicious individuals and organizations,” says Verlinden. “That is a complicated and tedious task, given the enormous amount of data involved and the fact that both the blacklists and the insurance policies are subject to frequent changes. For example, contracts must be rechecked upon all contractual modifications, such as the assignment of a new beneficiary. We must validate and document each modification.”

Finding a more efficient method

ERGO needed to find an efficient way to meet regulations without automating the process to the point where it would miss potential criminal activity.

“We were convinced that improving our efficiency would save us a substantial amount of money and time,” Verlinden says. “However, we were abundantly aware of the risks and pitfalls of total automation. For example, there is the issue of precisely matching our contractors with the suspicious individuals and organizations listed in the Dow Jones files we purchase. For instance, a given name can be spelled in a variety of ways, or with the addition of abbreviations, middle names and nicknames. We needed a powerful solution that is able to deal with these kinds of uncertainties.”

Matching big data for precise identification of suspects

Verlinden says the SAS solution manages enormous amounts of data and uses fuzzy logic analysis and a business rules approach that didn’t set off time-consuming false alerts. “Fuzzy logic enables the system to report matches between non-identical but textually, phonetically or numerically similar data records, including an assessment of the probability or quality of the match,” he says. “We also needed to precisely define the criteria that are required to generate an alert. This is essential if we are to successfully expose all suspicious records while avoiding false alerts as much as possible.

“Each day we check our database of 800,000 customers against the huge amount of proven and suspected ‘bad guys’ in the Dow Jones files. Thanks to fuzzy logic and fine-tuning of scenarios, we are able to reduce false positives to a level manageable for our investigator team. With SAS Anti-Money Laundering, we save precious time and money every day.”

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.